Harmonious Music-driven Group Choreography with Trajectory-Controllable Diffusion

Creating group choreography from music is crucial in cultural entertainment and virtual reality, with a focus on generating harmonious movements. Despite growing interest, recent approaches often struggle with two major challenges: multi-dancer collisions and single-dancer foot sliding. To address these challenges, we propose a Trajectory-Controllable Diffusion (TCDiff) framework, which leverages non-overlapping trajectories to ensure coherent and aesthetically pleasing dance movements. To mitigate collisions, we introduce a Dance-Trajectory Navigator that generates collision-free trajectories for multiple dancers, utilizing a distance-consistency loss to maintain optimal spacing. Furthermore, to reduce foot sliding, we present a footwork adaptor that adjusts trajectory displacement between frames, supported by a relative forward-kinematic loss to further reinforce the correlation between movements and trajectories. Experiments demonstrate our method's superiority.

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Publication Details

Journal
Proceedings of the AAAI Conference on Artificial Intelligence
Published
2025-04-11
DOI
https://doi.org/10.1609/aaai.v39i3.32268
Citations
2
Primary Topic
Music Technology and Sound Studies
Type
article
Field-Weighted Citation Impact
0.86
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article

Harmonious Music-driven Group Choreography with Trajectory-Controllable Diffusion

Ronghui Li, Jian Yang, Zeping Ren, Xiangzheng Zhou et al.
2 citations
Proceedings of the AAAI Conference on Artificial Intelligence
Music Technology and Sound Studies
0.86
article

Harmonious Music-driven Group Choreography with Trajectory-Controllable Diffusion

Ronghui Li, Jian Yang, Zeping Ren, Xiangzheng Zhou, Jun Li, Yuqin Dai, Wanlu Zhu, Jixuan Ying
article en
2 citations

Abstract

Creating group choreography from music is crucial in cultural entertainment and virtual reality, with a focus on generating harmonious movements. Despite growing interest, recent approaches often struggle with two major challenges: multi-dancer collisions and single-dancer foot sliding. To address these challenges, we propose a Trajectory-Controllable Diffusion (TCDiff) framework, which leverages non-overlapping trajectories to ensure coherent and aesthetically pleasing dance movements. To mitigate collisions, we introduce a Dance-Trajectory Navigator that generates collision-free trajectories for multiple dancers, utilizing a distance-consistency loss to maintain optimal spacing. Furthermore, to reduce foot sliding, we present a footwork adaptor that adjusts trajectory displacement between frames, supported by a relative forward-kinematic loss to further reinforce the correlation between movements and trajectories. Experiments demonstrate our method's superiority.

Proceedings of the AAAI Conference on Artificial IntelligenceVol. 39(3)
University Town of Shenzhen (CN), Nanjing University of Science and Technology (CN), Tsinghua University (CN)
Openalex Percentile: Top 28%
Music Technology and Sound Studies
0.86
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Harmonious Music-driven Group Choreography with Trajectory-Controllable Diffusion — Ronghui Li, Jian Yang, et al. · Proceedings of the AAAI Conference on Artificial Intelligence (2025) | TGRS Research Map | TGRS